package cn.doitedu.day02

import org.apache.spark.rdd.{RDD, ShuffledRDD}
import org.apache.spark.{Aggregator, HashPartitioner, SparkConf, SparkContext}

object T15_GroupByKeyDemo{

  def main(args: Array[String]): Unit = {

    //1.创建SparkConf
    val conf = new SparkConf().setAppName("MapPartitionsWithIndexDemo")
      .setMaster("local[4]")

    //2.创建SparkContext
    val sc = new SparkContext(conf)

    val lst = List(
      ("spark", 1), ("hadoop", 1), ("hive", 1), ("spark", 1),
      ("spark", 1), ("flink", 1), ("hbase", 1), ("spark", 1),
      ("kafka", 1), ("kafka", 1), ("kafka", 1), ("kafka", 1),
      ("hadoop", 1), ("flink", 1), ("hive", 1), ("flink", 1)
    )
    //通过并行化的方式创建RDD，分区数量为4
    val wordAndOne: RDD[(String, Int)] = sc.parallelize(lst, 4)

    val grouped: RDD[(String, Iterable[Int])] = wordAndOne.groupByKey()

    grouped.saveAsTextFile("out/out02")
  }


}
